It Takes a Village to Raise the Value of Big Data

There isn't always an expert with all the skills you need.

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For businesses, the days of the renaissance person have passed. Someone like a utility infielder who has some experience with a lot of functions used to be quite valuable because you could put them in wherever they were needed. But today’s organizations are so complex that they need people with expertise in very specific areas. These days it pays - frequently quite well - to be a specialist. For example, if you’re a data scientist, IT security expert, or computer engineer, there are people waiting to meet you in HR departments all across the globe.

But expertise can have its limits.

While it is always a good idea to have an expert doing what she or he is expert at, it is wrong to think that there is always an expert with all the skills you need. Especially when it comes to dealing with Big Data. This is one of the most complex, evolving, ambiguous, and important areas of business development today, and many companies are seeking a qualified expert to help them rein it in. But is acquiring one Big Data expert really the best path to success?

We’re at a time when the renaissance person is being replaced by the renaissance team. If you want to have success with your Big Data project, you need a group with many skill sets. So it’s important to recruit individuals with diverse capabilities which complement each other instead of spending your time searching for a mythical individual who can do it all. Of course the team has to include people who know math, statistics, and science - but those skills alone are not enough. After all, you can’t just point data scientists at your data and say “Go find stuff.”

You need to recruit people who can think about data in novel ways. So in addition to people who know about handling data, you also need people who know about your customers: their culture, their psychology, their behavior. To that end, you may want to consider onboarding a sociologist or others from the “soft” sciences.

When putting together your team, first figure out the skills you need and then find the people who have them, regardless of the field they’re in. This kind of team will be able to look at your data in a variety of ways. The people who are experts at handling data will give insights to those who understand your business needs and vice versa.

Having a variety of backgrounds and experiences is essential because there is no single way to interpret or process data. A collaborative, collective approach gives you greater insight into how your data analytics work. The sum of those unique perspectives is greater than the parts, and will continue to feed your decision-making power well into the future.

Of course there are some skills everyone on the team should have. They all need to be creative, able to handle ambiguity, and be effective at communicating. They should ideally possess some familiarity with the other teammates’ primary skill sets. It’s also good if your hard science types are a little unorthodox. A little bit of unconventional thinking can go a long way.

Data is like ore: Unless it is properly refined, shaped, and forged, it’s just a lump of rock. Doing everything needed to find the gold hidden inside is more than we can expect of any one person.